[1]}, [2]}, and [3]} proposed the idea of distant supervision to automatically create such text-tuple mapping without any human effort. In distant supervision, the tuples from an existing KB are mapped to a free text corpus such as Wikipedia articles or news articles (e.g., New York Times). The idea of distant supervision is that if a sentence contains two entities of a tuple from a KB, that sentence can be considered as the source of this KB tuple. On the other hand, if a sentence contains two entities from a KB and there is no relation between these two entities in the KB, that sentence is considered as a source of None tuple between the two entities. These None samples are useful as distantly supervised models consider only a limited set of positive relations. Any relation outside this set is considered as None relation. This method can give us a large number of tuple-to-text mappings which can be used to build supervised models for this task. This idea of distant supervision can be extended easily to single-document or multi-document relation extraction.
